Research Article
An Integrated Processing Method Based on Wasserstein Barycenter Algorithm for Automatic Music Transcription
@INPROCEEDINGS{10.1007/978-3-030-41117-6_19, author={Cong Jin and Zhongtong Li and Yuanyuan Sun and Haiyin Zhang and Xin Lv and Jianguang Li and Shouxun Liu}, title={An Integrated Processing Method Based on Wasserstein Barycenter Algorithm for Automatic Music Transcription}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II}, proceedings_a={CHINACOM PART 2}, year={2020}, month={2}, keywords={Automatic Music Transcription Machine learning Wasserstein Barycenter Ensemble NMF}, doi={10.1007/978-3-030-41117-6_19} }- Cong Jin
Zhongtong Li
Yuanyuan Sun
Haiyin Zhang
Xin Lv
Jianguang Li
Shouxun Liu
Year: 2020
An Integrated Processing Method Based on Wasserstein Barycenter Algorithm for Automatic Music Transcription
CHINACOM PART 2
Springer
DOI: 10.1007/978-3-030-41117-6_19
Abstract
Given a piece of acoustic musical signal, various automatic music transcription (AMT) processing methods have been proposed to generate the corresponding music notations without human intervention. However, the existing AMT methods based on signal processing or machine learning cannot perfectly restore the original music signal and have significant distortion. In this paper, we propose a novel processing method which integrates various AMT methods so as to achieve better performance on music transcription. This integrated method is based on the entropic regularized Wasserstein Barycenter algorithm to speed up the computation of the Wasserstein distance and minimize the distance between two discrete distributions. Moreover, we introduce the proportional transportation distance (PTD) to evaluate the performance of different methods. Experimental results show that the precision and accuracy of the proposed method increase by approximately 48% and 67% respectively compared with the existing methods.
